VarianceScaling

Initializer capable of adapting its scale to the shape of weights tensors.

With distribution=TRUNCATED_NORMAL or NORMAL, samples are drawn from a truncated/untruncated normal distribution with a mean of zero and a standard deviation (after truncation, if used) stddev = Math.sqrt(scale / n), where n is:

• number of input units in the weight tensor, if mode=FAN_IN
• number of output units, if mode=FAN_OUT
• average of the numbers of input and output units, if mode=FAN_AVG

With distribution=UNIFORM, samples are drawn from a uniform distribution within [-limit, limit], where limit = Math.sqrt(3 * scale / n);.

Examples:

      long seed = 1234l;
      float scale = 0.1f;
      VarianceScaling<TFloat32, TFloat32> initializer =
          new org.tensorflow.framework.initializers.VarianceScaling<>(
              tf, scale, Mode.FAN_IN, Distribution.UNIFORM, seed);
      Operand<TFloat32> values =
          initializer.call(tf.constant(Shape.of(2,2)), TFloat32.class);